code: def _make_all_unique_possible_pairs(
      ground_truth_dict: Dict,
  ) -> List[Tuple]:
      """
      Given a ground truth dictionary, generate all possible unique image pairs (both negative and positive pairs).
      """
      # get all elements of the dictionary
      all_files = list(ground_truth_dict.keys())
  
      # make all possible pairs (remove pairs with same elements)
      all_tuples = [
          i
          for i in itertools.product(all_files, all_files)
          if i[0] != i[1]
      ]
      return _get_unique_ordered_tuples(all_tuples)
  
file_path: imagededup/imagededup/handlers/metrics/classification.py
imports: import itertools
  from typing import Dict, List, Tuple
  import numpy
  from sklearn.metrics import classification_report, precision_score, recall_score, precision_recall_fscore_support
  from imagededup.utils.logger import return_logger
label_desc: Use image node_id 2 for calling a global function with example usage: _make_all_unique_possible_pairs(ground_truth_dict) and returns: _get_unique_ordered_tuples